Quantify commits

Quantified Commit Activity Over 14 Days

Developer	Avatar	Branches	PRs	Commits	Files	Changes
AMMAS1		1	1/1/0	2	6	640
Yijia Shao		1	0/0/0	2	1	18
Yucheng-Jiang		1	1/2/0	1	1	4

_{PRs: created by that dev and opened/merged/closed-unmerged during the period}

Report On: Fetch commits

Development Team and Recent Activity

Team Members and Their Recent Contributions

Yijia Shao (shaoyijia)

• Recent Contributions:
  • Updated README.md and merged pull requests related to the addition of a minimal user interface for developers and updates to README.md.
  • Involved in adding scripts and documentation to support customized retrieval sources (VectorRM).
  • Active in updating example scripts and integrating BingSearch.
  • Contributed to various other enhancements and fixes across the project.

Yucheng-Jiang

• Recent Contributions:
  • Updated README.md.
  • Involved in refactoring the codebase, syncing examples, and updating src.
  • Contributed to updating evaluation data paths and creating prompts for Prometheus evaluation.

AMMAS1

• Recent Contributions:
  • Added scripts and documentation to support customized retrieval sources (VectorRM).
  • Made specific updates to ensure users provide unique URLs when using VectorRM.

Patterns, Themes, and Conclusions

• Collaboration: There is evident collaboration among team members, especially in areas concerning the integration of new features like VectorRM and updates to documentation and README files.
• Focus Areas:
  • Interface Enhancements: Recent activities show a focus on improving user interfaces, specifically for developers, which suggests an emphasis on making the system more accessible and easier to use for development purposes.
  • Customization and Flexibility: The addition of scripts to support customized retrieval sources indicates a push towards making the system more flexible and adaptable to different use cases.
• Commitment to Quality: Frequent updates to documentation and example scripts, along with quick fixes and enhancements, demonstrate a commitment to maintaining a high-quality, robust system.
• Engagement with Community: The team is responsive to community contributions and external inputs as seen by their activity in merging pull requests from other contributors. This engagement likely helps in improving the system based on user feedback and external expertise.

Overall, the development team is actively enhancing the system's flexibility, usability, and quality while engaging with the broader community to incorporate a diverse set of improvements.

Report On: Fetch issues

Recent Activity Analysis

The recent GitHub issue activity for the project stanford-oval/storm shows a diverse range of issues from bug reports and feature requests to integration proposals and setup problems. Notably, the issues span various aspects of the project including language support, API integrations, and operational errors.

Notable Issues:

1. Language and Localization Concerns: Issues like #63 request additional features such as multi-language support for outputs, indicating a need for the project to cater to a global user base.

2. Technical Challenges and Bugs: Several issues report technical difficulties such as #62 and #28 where users encounter index errors and unexplained service disruptions. These issues are critical as they directly impact the usability of the project.

3. Integration Requests: Issues like #48 show a demand for integrating more sophisticated models (Groq LLM), suggesting that users are looking for advanced capabilities in the project.

4. Operational and Setup Issues: Problems with setup and operation are common, as seen in issues like #42 and #31, where users struggle with missing packages and unclear instructions.

5. Feature Requests: There is a clear interest in extending the project's functionality, evidenced by issues like #41 requesting a web service interface, which suggests a demand for more accessible interfaces for broader use.

Common Themes:

• Enhancement Requests: Many issues focus on enhancing the project with new features or integrations, indicating active engagement and interest in expanding the project’s capabilities.
• Setup and Configuration Problems: A significant number of issues arise from setup challenges, pointing to potential improvements needed in documentation and user guidance.
• Technical Bugs and Errors: Persistent technical issues suggest that stability and error handling could be improved to enhance user experience.

Issue Details

Most Recently Created Issues:

• #63: Provide other language output

  • Priority: High
  • Status: Open
  • Created: 1 day ago

• #62: SentenceTransformer IndexError: list index out of range

  • Priority: High
  • Status: Open
  • Created: 1 day ago

Most Recently Updated Issues:

• #28: root: Error : Error occurs

  • Priority: High
  • Status: Open
  • Created: 80 days ago
  • Edited: 9 days ago

• #49: Error occur in living demo

  • Priority: Medium
  • Status: Open
  • Created: 41 days ago
  • Edited: 38 days ago

These issues highlight ongoing challenges with error handling, feature requests for localization, and operational bugs that affect user experience. Addressing these could significantly improve the robustness and appeal of the project.

Report On: Fetch pull requests

Analysis of Pull Requests for the Stanford-Oval/Storm Repository

Open Pull Requests

PR #20: Support DuckDuckGoSearchAPI and TavilySearchAPI as Alternatives to You.com

• Status: Open
• Age: 87 days since creation, last edited 15 days ago.
• Summary: This PR aims to integrate additional search APIs (DuckDuckGoSearchAPI and TavilySearchAPI) into the project, providing alternatives to the default You.com search API. It also includes changes that allow these APIs to return complete contents instead of just snippets.
• Discussion Points:
  • There's an ongoing discussion about potential integration issues with OpenAI models, specifically connection errors reported by a user.
  • The PR is being held pending a major update to the repository, as indicated by Yijia Shao in the comments. This could affect the mergeability of the PR depending on the changes in the upcoming major update.
• Concerns:
  • The PR has been open for a long time (87 days), which might indicate difficulties in integration or pending decisions regarding the direction of the project's API support.

PR #17: [doc] Add readme-zh for Chinese users

• Status: Open
• Age: 88 days since creation, last edited 77 days ago.
• Summary: Addition of a Chinese version of the README file to make the project more accessible to Chinese-speaking users.
• Discussion Points:
  • Yijia Shao has mentioned that this PR will be held as there are upcoming major updates that might change the main README.md file significantly.
• Concerns:
  • Similar to PR #20, this PR has been open for a long time without merging, likely due to pending updates that could affect the documentation.

Recently Closed Pull Requests

PR #59: Update README.md

• Status: Closed and merged 4 days ago.
• Summary: Minor updates to README.md, including new entries under "Latest News."
• Significance: Indicates active development and updates being documented promptly.

PR #58: add scripts and documentation to support customize retrieval source

• Status: Closed and merged 5 days ago.
• Summary: This significant update allows users to provide their own data sources for content retrieval, enhancing customization capabilities of the Storm platform.

PR #54: auto-sync-2024-06-18-21-04-23

• Status: Closed and merged 7 days ago.
• Summary: Automated sync that included significant additions such as a new minimal user interface built with Streamlit.

Notable Unmerged PRs:

PR #53: auto-sync-2024-06-18-20-58-09

• Status: Closed but not merged.
• Summary: Another automated sync attempt that appears to have been superseded by later successful merges (e.g., PR #54).

PR #44: Update to gpt-4-turbo

• Status: Closed but not merged.
• Summary: Proposed updates to utilize GPT-4 Turbo models in example scripts. Not merging this might suggest compatibility or stability concerns with these models at the time of review.

Summary

The open pull requests, especially PR #20 and PR #17, are significant due to their potential impact on the project's functionality and accessibility but are currently on hold pending major updates. The recently closed pull requests show a healthy pace of documentation updates and feature enhancements. However, some pull requests like PR #53 and PR #44 were closed without merging, which might indicate shifting priorities or unresolved issues with those changes.

Report On: Fetch Files For Assessment

Analysis of Source Code Files

1. src/rm.py

Overview

This Python module defines several classes for retrieval models (YouRM, BingSearch, VectorRM) that interface with different data sources (You.com API, Bing Search API, and a custom Qdrant vector store). These classes inherit from a base class dspy.Retrieve and are designed to fetch relevant documents based on input queries.

Key Observations

• Class Structure: Each class (YouRM, BingSearch, VectorRM) is well-encapsulated, handling specific retrieval tasks. This modular design facilitates easy extension or modification.
• Error Handling: Proper error handling is implemented, especially in network requests and API interactions, which enhances robustness.
• Logging: The use of logging for error reporting in catch blocks helps in debugging and maintaining the code.
• Environment Variables: The code uses environment variables for sensitive information like API keys, which is a good security practice.
• Validation: There is a mechanism to validate URLs through a callable passed during initialization, which adds flexibility in filtering results.

Potential Improvements

• Hardcoded URLs and Parameters: Some API parameters and endpoints are hardcoded. These could be externalized to configuration files or environment variables for easier management.
• Exception Handling: Broad exception clauses (except Exception as e) could be more specific to handle only anticipated exceptions. This would prevent masking other unexpected issues.
• Documentation: While basic comments are present, more comprehensive docstrings detailing parameters, return types, and exceptions could improve maintainability and usability.

2. examples/run_storm_wiki_gpt_with_VectorRM.py

Overview

This script demonstrates how to set up and run the STORM system using the GPT models and a custom retrieval model (VectorRM). It includes detailed setup for various components like language models and retrieval systems.

Key Observations

• Argument Parsing: Uses argparse to handle command-line arguments which makes the script flexible and user-configurable.
• Environment Configuration: Loads configuration from environment variables and ensures all necessary settings are in place before proceeding.
• Modular Language Model Setup: Configures different components of the language model separately, allowing fine-tuned control over each aspect of the language processing.

Potential Improvements

• Error Handling: The script could benefit from more robust error handling around file operations and network requests.
• Configuration Management: Externalizing configurations such as model names and device settings could make the script easier to adapt to different environments or requirements.
• Logging: Adding logging would help track the flow of execution and errors, especially useful during deployment or when used by end-users unfamiliar with the codebase.

3. frontend/demo_light/demo_util.py

Overview

This module provides utility functions for file operations, text processing, and UI components specifically tailored for a Streamlit frontend demonstrating the STORM system.

Key Observations

• Utility Functions: Includes a wide range of helper functions for file reading/writing, date manipulation, and text formatting which supports various frontend needs.
• Integration with Streamlit: Functions are designed to work seamlessly with Streamlit for displaying content, handling user inputs, etc., demonstrating good integration practices.
• Markdown and HTML Processing: Contains functions to handle markdown content and generate HTML dynamically, which is crucial for content presentation in the demo.

Potential Improvements

• Code Organization: The file is quite large with diverse functionalities; splitting into smaller modules (e.g., file handling, UI helpers) could improve maintainability.
• Exception Handling: More comprehensive error checking and handling would make the utilities robust against malformed inputs or file access issues.
• Testing: Adding unit tests for these utility functions would ensure their reliability, especially since they interact heavily with the filesystem and external libraries.

Conclusion

The analyzed files demonstrate a well-thought-out structure with clear separation of concerns and adherence to good coding practices like modularity and security-awareness. However, improvements in areas such as configuration management, error handling, documentation, and testing would further enhance the code quality and maintainability.